Seismic data obtained in field surveys include signals from subterranean formations, and also noise. The signals are produced by acoustic reflections or refractions from rock layers below the surface of the earth. Most raw land and marine seismic data closely conform to a reflection signal plus additive and/or convolutional noise model. The noise may be due to a number of sources such as power lines, motor vibrations and animal noise. In marine data, everything from swell, tow and propeller noise to shot generated direct waves, refractions and multiples to shipping, cetacean and other seismic crews act as additive noise relative to a reflected signal. Convolutional noise sources, like source and receiver coupling, processing and system noise are types of noise that also have to be accommodated. The different types of noise compromise the effectiveness of the end results of the processing of seismic data because the noise can overwhelm the signal. In such cases, the signal can be difficult, if not impossible, to interpret and quantify.
Diversity noise attenuation methods were invented in the mid 1960's by Geophysical Services Inc. (GSI) and were successfully used to extract signals from vibroseis sweep data recorded in areas having extreme amounts of cultural noise. The underlying principle of diversity noise attenuation is that seismic data are composed of nearly uniform strength signals and large amounts of additive noise. For vibroseis sweeps, samples are weighted inversely proportional to a local estimate of noise power before being summed with other sweeps. The less power in an arrival, the more likely that the arrival is signal.
Methods for improving the S/N ratio in seismic data are described in numerous patents. For example, one method is taught by U.S. Pat. No. 3,398,396 to Embree. This method utilizes the amplification of each trace as a function of the inverse ratio of the total power in each trace as compared to another trace. The amplified traces are then combined into a group of modified traces. Embree also suggests that input seismic data may be weighted in dependence upon the power in frequency components or bands. The signals, separated based on frequencies, are modulated on a frequency dependent noise based correcting function and are then summed to produce enhanced output traces.
A second method is taught by U.S. Pat. No. 5,138,583 to Wason et al. This method provides for attenuation of coherent and incoherent noise in seismic signals. Seismic signal data are transformed from a time-space domain using a Radon-transform domain. In the Radon-transform domain, coherent noise is attenuated by muting and incoherent noise is attenuated by diversity stacking. Data remaining in the Radon-transform domain are transformed back to the time-space domain by an inverse Radon transform.
Each of these methods has shortcomings. These methods do not produce output trace amplitudes preserving true relative signal amplitude within the total seismic data set. These previous methods approximate noise power with total trace power which incorrectly alters relative signal amplitudes. True relative signal amplitude refers to the changes in signal component of the output amplitude being directly proportional to relative changes in subsurface interface reflection coefficient. Another shortcoming is the restrictions of these methods to certain data coordinates such as common source receiver geometry or Radon data coordinates. Further, weighting schemes in these methods do not provide data adaptive parameterization of noise estimation. There is a need for a method of enhancing the S/N ratio of seismic data which overcomes the shortcomings of the above described methods. The present invention provides a method which addresses this need.